Using the methods described by Chris in the entry below – i.e. at

http://iloapp.thejll.com/blog/earthshine?Home&post=265

I have also selected for the likely good data by taking extinction into account and looking for linear sequences. This resulted in a set of images that I deem ‘good’. That list can be compared to Chris’ list.

Chris has 3162 ‘good’ images, while I have 2990. The cross between the lists finds 2273 instances on both lists. This list of ‘jointly agreed good images’ is here:


txt

Methods for selecting good images differ slightly: Chris does not yet consider the alpha value found in the EFM method – I select for alphas in a narrow range near the mode of the distribution for each filter.

With converging selection criteria the list above would expand somewhat – perhaps best to keep the criteria a little different to avoid duplication of potential errors.

The joint list contains 49 unique nights. The distribution of images over nights is:

58 2455856
363 2455857
404 2455858
33 2455859
228 2455864
65 2455865
276 2455917
173 2455923
117 2455924
11 2455938
6 2455940
15 2455943
10 2455944
5 2455945
2 2456000
3 2456001
8 2456002
9 2456003
3 2456004
6 2456005
4 2456006
5 2456014
31 2456015
54 2456016
34 2456017
3 2456027
4 2456028
16 2456029
11 2456030
10 2456031
7 2456032
15 2456034
2 2456035
26 2456045
49 2456046
27 2456047
20 2456061
2 2456062
5 2456063
3 2456064
35 2456073
21 2456074
31 2456075
11 2456076
7 2456090
12 2456091
9 2456092
6 2456093
18 2456104

where the first column gives the number for the night. Note that towards the end of the sequence there are few images per night – that is because we were realizing the necessity to observe ‘stacks’ rather than sequences of single images which results in fewer co-added images.


A histogram of these data is shown above.